An approach for estimating net primary productivity and ......Review An approach for estimating net primary productivity and annual carbon inputs to soil for common agricultural crops

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AnapproachforestimatingnetprimaryproductivityandannualcarboninputtosoilforcommonagriculturalcropsinCanada

ArticleinAgricultureEcosystems&Environment·January2007

ImpactFactor:3.4·DOI:10.1016/j.agee.2006.05.013

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MaBolinder

SwedishUniversityofAgriculturalSciences

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H.H.Janzen

AgricultureandAgri-FoodCanada


SEEPROFILE

E.G.Gregorich



SEEPROFILE

BertVandenbygaart



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Review

An approach for estimating net primary productivity and annual carbon

inputs to soil for common agricultural crops in Canada

M.A. Bolinder a,*, H.H. Janzen b, E.G. Gregorich c, D.A. Angers a, A.J. VandenBygaart c

a Soils and Crops Research and Development Centre, Agriculture and Agri-Food Canada,

2560 Hochelaga Blvd, Sainte-Foy, Que., Canada G1V 2J3b Lethbridge Research Centre, Agriculture and Agri-Food Canada, 5403 1st Avenue South, Lethbridge, Alta., Canada T1J 4B1

c Eastern Cereal and Oilseed Research Centre, Agriculture and Agri-Food Canada,

KW Neatby Building, 960 Carling Avenue, Ottawa, Ont., Canada K1A 0C6

Received 22 November 2005; received in revised form 20 April 2006; accepted 3 May 2006

Available online 23 June 2006

www.elsevier.com/locate/agee

Agriculture, Ecosystems and Environment 118 (2007) 29–42

Abstract

The current interest in characterizing, predicting and managing soil C dynamics has focused attention on making estimates of C inputs to

soil more accurate and precise. Net primary productivity (NPP) provides the inputs of carbon (C) in ecosystems and determines the amount of

photosynthetically fixed C that can potentially be sequestered in soil organic matter. We present a method for estimating NPP and annual C

inputs to soil for some common Canadian agroecosystems, using a series of plant C allocation coefficients for each crop type across the

country. The root-derived C in these coefficients was estimated by reviewing studies reporting information on plant shoot-to-root (S:R) ratios

(n = 168). Mean S:R ratios for annual crops were highest for small-grain cereals (7.4), followed by corn (5.6) and soybeans (5.2), and lowest

for forages (1.6). The review also showed considerable uncertainty (coefficient of variation for S:R ratios of�50% for annual crops and�75%for perennial forages) in estimating below-ground NPP (BNPP) in agroecosystems; uncertainty was similar to that for Canadian boreal forests.

The BNPP (including extra-root C) was lower for annual crops (�20% of NPP) than for perennial forages (�50%). The latter was similar toestimates for relative below-ground C allocation in other Canadian natural ecosystems such as mixed grasslands and forests. The proposed

method is easy to use, specific for particular crops, management practices, and driven by agronomic yields. It can be readily up-dated with new

experimental results and measurements of parameters used to quantify the accumulation and distribution of photosynthetically fixed C in

different types of crops.

# 2006 Elsevier B.V. All rights reserved.

Keywords: Roots; C inputs; C allocation; Uncertainty; Agroecosystems; Natural ecosystems

Contents

1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30

2. Estimates of root biomass in Canadian agroecosystems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30

2.1. Description of experiments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30

2.2. Sampling procedures and methods for root separation. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32

2.3. Shoot-to-root ratios and sampling depth . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34

3. Proposed method for estimating total annual NPP, C allocation, and C input to soil . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35

3.1. NPP and C allocation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35

3.2. Annual C inputs to soil . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36

3.3. Assumptions used in calculations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36

* Corresponding author. Tel.: +1 418 657 7985x271; fax: +1 418 648 2402.

E-mail address: [email protected] (M.A. Bolinder).

0167-8809/$ – see front matter # 2006 Elsevier B.V. All rights reserved.doi:10.1016/j.agee.2006.05.013

mailto:[email protected]://dx.doi.org/10.1016/j.agee.2006.05.013

M.A. Bolinder et al. / Agriculture, Ecosystems and Environment 118 (2007) 29–4230

3.3.1. Harvest index. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36

3.3.2. Shoot:root ratios. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36

3.3.3. Extra-root C . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37

4. Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38

4.1. Relative C allocation coefficients for Canadian agroecosystems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38

4.2. Quantitative estimates of annual C inputs to soil and NPP . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39

4.3. Uncertainty associated with estimates of BNPP . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39

5. Conclusions. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41

Acknowledgement . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41

References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41

1. Introduction

Increases in the concentration of CO2 in the atmosphere

have prompted renewed interest in increasing the stocks of

carbon (C) in the world’s croplands to mitigate climate

change and also improve soil quality (IPCC, 2000; Lal,

2004a,b). To better characterize, predict and manage soil C

dynamics, we need more precise and accurate estimates of C

inputs to soil. The C fixed in plants by photosynthesis and

added to soil as above- and below-ground litter, is the

primary source of C in ecosystems (Warembourg and Paul,

1977). Predicting the changes in C stocks (notably in soils),

therefore, depends on reliable estimates of net primary

productivity (NPP) and the proportion of the NPP returned to

the soil (Paustian et al., 1997; Grogan and Matthews, 2002;

Bolinder et al., 2006; Campbell et al., 2000; Izaurralde et al.,

2001). The concept and definition of NPP varies in the

literature. Scurlock and Olson (2002) defined NPP as the

increase in plant mass plus losses (such as mortality,

herbivory, etc.), summed for both above- and below-ground

compartments per unit area of ground per unit of time.

The annual NPP in agroecosystems, and the distribution of

C in plant parts, is usually calculated from agricultural yield,

the plant component most often measured. In cereal crops, for

example, C inputs from post-harvest above-ground residue

(i.e., straw) is estimated from grain yields using ‘harvest

index’ values or related regression relationships, and below-

ground C inputs are calculated from shoot-to-root (S:R) ratios

(Bolinder, 2004; Campbell et al., 2000). While such

approaches have been useful, better estimates of crop NPP

are needed to adequately assess regional and national

contributions of agriculture to the global C budget (Prince

et al., 2001).

The largest uncertainty in deriving NPP may originate in

estimates of below-ground NPP (BNPP), including inputs

from roots, exudates, and other root-derived organic

material from root-turnover (root hairs and fine roots that

are sloughed during the growing season). Though a large

proportion of NPP is allocated to below-ground plant parts

(Li et al., 2003; Stanton, 1988), the amount of BNPP is one

of the most poorly understood attributes of terrestrial

ecosystems (Laurenroth, 2000). Quantifying these below-

ground C inputs, notably from exudates and other ephemeral

root-derived materials, is difficult and remains a research

priority (Balesdent and Balabane, 1996; Gill et al., 2002;

Grogan and Matthews, 2002; Kurz et al., 1996; Kuzyakov

and Domanski, 2000).

Our objective was to develop a set of coefficients for

estimating total annual NPP, C allocation patterns, and

annual C inputs to soil for common agricultural crops in

Canada. To do this, we outline a broadly applicable approach

for expressing NPP and C allocation in plants, with an

emphasis on BNPP, and provide estimates of coefficients,

based on a review of the literature, largely from Canadian

studies. This approach, using values easily updated, can then

be used in modelling efforts to estimate soil C changes in

agricultural soils of Canada.

2. Estimates of root biomass in Canadian

agroecosystems

We reviewed data from studies with field measurements of

shoot and root biomass at or near plant maturity (i.e., harvest),

considering only studies published after 1970. Most of the

studies were conducted in Canada, though some U.S. studies

were included when Canadian data were insufficient and the

climate was similar to that in Canada (Tables 1 and 2).

2.1. Description of experiments

The crops in all studies were usually fertilized according

to local recommendations, except where the experiment

involved fertilizer treatments. Most of the data we used were

from studies with conventional experimental designs (i.e.,

randomized-block, split–plot, split–split–plot and criss–

cross) with two to five replicates. Only a few studies

involved a field (Soon, 1988; Allmaras et al., 1975), or

unreplicated field-plots (Buyanovsky and Wagner, 1986;

Kisselle et al., 2001) sub-divided to provide pseudo-

replicated experimental units. The number of sub-samples

taken for root biomass measurements from each experi-

mental unit (which were subsequently averaged) varied from

one to six, but usually one to two sub-samples were taken.

Where possible, we reported or calculated S:R ratios at the

treatment level. The data reported for the study by Bowren

et al. (1969) on forages (Table 2) were averaged across

fertilized and unfertilized treatments (effects were not

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M.A. Bolinder et al. / Agriculture, Ecosystems and Environment 118 (2007) 29–42 31

Table 1

Shoot to root ratios measured at or close to maturity in field studies for small-grain cereals, corn and soybeans in Canada and the U.S.

Location Species Cultivar Treatment/experiment Texture Sampling

procedure

Sampling

depth (cm)

Shoot/root

ratio

Reference

Cooking

Lake, Alta.

SW Roblin Simulated

erosion (0 cm)

NR Soil cores 40 10.6 Izaurralde

et al. (1992)

Simulated

erosion (20 cm)

4.6

Check 4.3

Manure 8.6

Fertilizer 8.8

Josephburg, Alta. SW Roblin Simulated

erosion (0 cm)

NR Soil cores 40 11.8

Simulated

erosion (20 cm)

7.3

Check 6.5

Manure 10.6

Fertilizer 11.6

Southwestern

Saskatchewan

SW Manitou Natural

rainfall; 0 kg N

L Lysimeters 120 5.7 Campbell and

de Jong (2001)

Natural

rainfall; 20.5 kg N

4.5

Natural

rainfall; 41 kg N

5.2

Natural

rainfall; 61.5 kg N

5.5

Natural

rainfall; 82 kg N

5.6

Natural

rainfall; 123 kg N

5.9

Natural

rainfall; 164 kg N

6.0

Irrigated; 0 kg N 5.5

Irrigated; 20.5 kg N 7.1


Irrigated; 61.5 kg N 6.5




Ottawa, Ont. WW Harus Recommendation trials CL Soil cores 30 4.9 Bolinder

et al. (1997)AC-Ron Recommendation trials 4.9

Casey Recommendation trials 4.9

Quebec, Que. WW Borden Recommendation trials C Soil cores 30 7.7

Lennox Recommendation trials 6.8

Valor Recommendation trials 6.5

Central

Missouri (U.S.)

WW Caldwell 1981 measurement SiL Soil cores 50 1.2 Buyanovsky and

Wagner (1986)1982 measurement 1.1

1984 measurement 1.1

Ellerslie, Alta. B Empress 15N study SiCL Cylinders 30 8.1 Rutherford and

Juma (1989)Breton, Alta. B 15N study SiL Cylinders 30 4.8

Ellerslie, Alta. B Abee 14C study SiC Cylinders 50 17.1 Xu and Juma

(1993)Samson 14C study 15.8

Ellerslie, Alta. B Abee 1989 measurement NR Soil cores 40 11.8 Xu and Juma

(1992)Bonanza 1989 measurement 11.5

Harrington 1989 measurement 11.3

Samson 1989 measurement 10.3

Abee 1990 measurement 12.5

Bonanza 1990 measurement 10.7

Harrington 1990 measurement 10.4

Samson 1990 measurement 9.4

Ellerslie, Alta. B Empress Conventional tillage SiCL Cylinders 30 11.9 Haugen-Kozyra

et al. (1993)Zero tillage 13.4


Table 1 (Continued )

Location Species Cultivar Treatment/experiment Texture Sampling

procedure

Sampling

depth (cm)

Shoot/root

ratio

Reference

Ellerslie, Alta. B NR Diverse cropping systems SiL Soil cores 40 8.3 Izaurralde

et al. (1993)Breton, Alta. B NR Diverse cropping systems L 8.3

Beaverlodge, Alta. B Galt Spatial distribution study SiL Soil cores 90 6.7 Soon (1988)

Ottawa, Ont. B Leger Recommendation trials CL Soil cores 30 2.0 Bolinder

et al. (1997)Chapais Recommendation trials 1.7

Codac Recommendation trials 2.3

Ottawa, Ont. O Ultima Recommendation trials CL Soil cores 30 2.4 Bolinder

et al. (1997)Lotta Recommendation trials 2.5

Rigodon Recommendation trials 2.7

Quebec, Que. T Wintri Recommendation trials C Soil cores 30 5.1 Bolinder

et al. (1997)Trillium Recommendation trials 5.6

Kansas (U.S.) GS Moench Hybrid and backcross study SiL Excavated NR 11.6 Piper and

Kulakow (1994)

Saint-Hyacinthe, Que. GC Pride 15N study SL, CL Excavation 25 11.2 Tran and

Giroux (1998)

Saint-Lambert, Que. SC Hyland 15N study SiL, SL 10.0

Montreal, Que. GC Pioneer Low fertility site FSL Soil cores 60 8.1 Zan et al. (2001)

GC Pioneer High fertility site 8.5

Southwestern

Missouri (U.S.)

GC DeKalb Water relationships study SC Excavation 152 5.7 Allmaras

et al. (1975)

Mead, NE (U.S.) GC Four

genotypes

0 kg N SiCL Soil cores 90 5.2 Eghball and

Maranville (1993)60 kg N 6.3

120 kg N 7.8

180 kg N 6.9

Dryland 5.6

Irrigated 7.5

Clarksville, MD

(U.S.)

GC Pioneer 1982: 0 kg N SL Soil cores 60 3.9 Anderson (1988)

1982: 180 kg N 6.7

1983: 0 kg N 2.5

1983: 180 kg N 4.8

1984: 0 kg N 2.6

1984: 180 kg N 5.6

Central

Missouri (U.S.)

GC Pioneer 1981 measurement SiL Soil cores 50 1.4 Buyanovsky

and Wagner (1986)1982 measurement 0.9

Horseshoe

Bend, GA (U.S.)

GC NR Conventionnal tillage NR Soil cores 15 2.8 Kisselle

et al. (2001)No-tillage 3.2

Fayetteville,

AR (U.S.)

SYBN Forrest Root competition SiL Cylinder 20 8.0 Marvel

et al. (1992)No root competition 8.0

Southwestern

Missouri (U.S.)

SYBN Harosoy (D) Water relationships study SC Excavated 152 7.0 Allmaras

et al. (1975)Harosoy (I) 5.3

Central

Missouri (U.S.)

SYBN Merrill 1981 measurement SiL Soil cores 50 1.8 Buyanovsky

and Wagner (1986)1982 measurement 1.2



Ashland,

KS (U.S.)

SYBN Williams Irrigated SiL Excavated 180 8.1 Mayaki

et al. (1976)Non irrigated 4.8

Horseshoe Bend,

GA (U.S.)

SYBN Bragg Conventionally tilled L Excavated 30 8.0 House

et al. (1984)No-tilled 7.9

Species: SW, spring wheat; WW, winter wheat; B, barley; O, oats; T, triticale; GS, grain–sorghum; GC, grain–corn; SC, silage–corn; SYBN, soybeans. Textural

class: F, fine; S, sand; L, loam; C, clay; Si, silt.

significant) and across sites. The forage data from Kunelius

et al. (1992) are averages from five small-plot experiments

over 3 years, and the data for corn (Zea mays L.) (Table 1)

from Eghball and Maranville (1993) are averages for four

hybrids.

2.2. Sampling procedures and methods for root

separation

Procedures used to sample roots in these field experi-

ments included extraction of soil cores, excavation


Table 2

Shoot to root ratios measured at or close to maturity in field studies for cultivated forages in Canada and the U.S

Location Species Cultivar Treatment/experiment

(growth stage)

Texture Sampling

procedure

Sampling

depth (cm)

Shoot/root

ratio

Reference

Ellerslie,

Alta.

F (Grass sp.) Creeping red (1st PY) SiL Soil cores 40 1.3 Izaurralde

et al. (1993)

Breton,

Alta.

L 0.9

Melfort,

Sask.

SC (Leg sp.) Erector Fertilized and unfertilized

combined (2nd, 3rd, and

4th PY combined)

SiC Excavated 20 4.1 Bowren

et al. (1969)A (Leg sp.) Ladak 1.2

RC (Leg sp.) Altaswede 3.1

White fox,

Sask.

SC (Leg sp.) Erector FSL 4.8

A (Leg sp.) Ladak 1.9

RC (Leg sp.) Altaswede 3.2

Swift current,

Sask.

BG (Grass sp.) Leyss. 0 kg N (ES, 20 years) SiC

to CL

Soil cores 90 0.3 Leyshon

(1991)50 kg N (ES, 20 years) 0.4

100 kg N (ES, 20 years) 0.7

200 kg N (ES, 20 years) 0.8

Outlook,

Sask.

BG (Grass sp.) Fleat Monocropped (EYPS) SL Excavated 30 0.2 Walley

et al. (1996)Monocropped (1st PY) 0.4

Monocropped (2nd PY) 0.1

BG (Mix.) Fleat Intercropped (EYPS) 0.5

Intercropped (1st PY) 0.5

Intercropped (2nd PY) 0.3

A (Leg sp.) Beaver Monocropped (EYPS) 0.4

Monocropped (1st PY) 0.7

Monocropped (2nd PY) 0.7

A (Mix.) Beaver Intercropped (EYPS) 0.7

Intercropped (1st PY) 1.0

Intercropped (2nd PY) 1.0

Montreal,

Que.

SG (Grass sp.) Cave-In-Rock Low fertility site (3rd PY) FSL Soil cores 60 1.7 Zan et

al. (2001)High fertility site (3rd PY) 2.6

PEI IR (Grass sp.) Lemtal Small plot study (EYPS) FSL Excavated 18 2.9 Kunelius

et al. (1992)WR (Grass sp.) Aubade Small plot study (EYPS) 4.4

RC (Leg sp.) Florex Small plot study (EYPS) 2.3

Charlottetown,

PEI

IR (Grass sp.) Lemtal 1987 measurement (EYPS) FSL Excavated 18 1.3 Carter

et al. (2003)1988 measurement (EYPS) 1.2

1989 measurement (EYPS) 0.8






RC (Leg sp.) Florex 1987 measurement (EYPS) 1.7








Fredericton,

NB

OG (Grass sp.) Kay 1995 measurement (1st PY) FSL Soil cores 45 1.3 Bolinder

et al. (2002)F (Grass sp.) NR 1995 measurement (1st PY) 1.6

BG (Grass sp.) Radisson 1995 measurement (1st PY) 1.7

CG (Grass sp.) Palaton 1995 measurement (1st PY) 1.0

T (Grass sp.) Champ 1995 measurement (1st PY) 1.2

R (Grass sp.) Riika 1995 measurement (1st PY) 1.5

SG (Grass sp.) Trailblazer 1995 measurement (1st PY) 1.2

RC (Leg sp.) Florex 1995 measurement (1st PY) 1.0

A (Leg sp.) Apica 1995 measurement (1st PY) 1.4


Table 2 (Continued )

Location Species Cultivar Treatment/experiment

(growth stage)

Texture Sampling

procedure

Sampling

depth (cm)

Shoot/root

ratio

Reference

Fredericton,

NB

OG (Grass sp.) Kay 1996 measurement (2nd PY) FSL Soil cores 45 0.7 Bolinder

et al. (2002)F (Grass sp.) NR 1996 measurement (2nd PY) 0.5

BG (Grass sp.) Radisson 1996 measurement (2nd PY) 0.8

CG (Grass sp.) Palaton 1996 measurement (2nd PY) 0.5

T (Grass sp.) Champ 1996 measurement (2nd PY) 0.5

R (Grass sp.) Riika 1996 measurement (2nd PY) 0.4

SG (Grass sp.) Trailblazer 1996 measurement (2nd PY) 0.5

RC (Leg sp.) Florex 1996 measurement (2nd PY) 0.8

A (Leg sp.) Apica 1996 measurement (2nd PY) 0.9

Rosemount,

MN (U.S.)

A (Leg sp.) Answer (EYPS, 1st PY and

2nd PY combined)

SiL Excavated 30 1.4 Sheaffer

et al. (1991)RC (Leg sp.) Florex 1.2

BT (Leg sp.) Leo 1.1

PEI IR (Grass sp.) Lemtal Small plot study (EYUS) SL Excavation 18 2.3 Kunelius

et al. (1992)IR (Grass sp.) Barmultra Small plot study (EYUS) 1.2

WR (Grass sp.) Aubade Small plot study (EYUS) 2.3

WR (Grass sp.) Marshall Small plot study (EYUS) 4.8

RC (Leg sp.) Florex Small plot study (EYUS) 4.6

IR (Grass sp.) Lemtal Large plot study (EYUS) FSL Excavation 18 2.4

IR (Grass sp.) Barmultra Large plot study (EYUS) 2.7

WR (Grass sp.) Aubade Large plot study (EYUS) 2.3

WR (Grass sp.) Marshall Large plot study (EYUS) 5.0

RC (Leg sp.) Florex Large plot study (EYUS) 3.7

Species: F, fescue; SC, sweet clover; A, alfalfa; RC, red clover; BG, bromegrass; SG, switchgrass; IR, Italian ryegrass; WR, esterwolds ryegrass; OG,

orchardgrass; CG, canarygrass; T, timothy; R, ryegrass; BT, birdsfoot trefoil (Grass sp., grass species; Leg sp., legume species; Mix., mixture of grass and

legume species). Growth stage: EYPS, establishment year pure seeded; EYUS, establishment year under-seeded; PY, production year (years (s) after

establishment); ES, established stand. Textural class: F, fine; S, sand; L, loam; C, clay; Si, silt.

techniques which involved removal of sections or

blocks of soils of varying sizes (e.g., 20 cm � 30 cm,30 cm � 70 cm, and 100 cm � 75 cm), and, in one case,lysimeters. Piper and Kulakow (1994), in a grain–sorghum

(Sorghum bicolour) cropping system (Table 1) used an

excavation procedure involving the removal of entire

plants. Most estimates of root biomass were made on

light-textured soils (i.e.,


Fig. 1. An illustration, for two conceptualized plants, of the proposed C

pools, for quantifying annual C allocation in crop plants. CP = C in ‘product’

(e.g., grain, forage, tuber); CS = C in above-ground residue (e.g, straw,

stover, chaff); CR = C in roots (not including that fraction designated as

‘product’); CE = extra-root C (including all root-derived materials not

usually recovered in the ‘root’ fraction). For forage crops (not shown),

CP is C in all above-ground plant parts (i.e., CS = 0).

1986; Izaurralde et al., 1993; Xu and Juma, 1993), but for

only 60% in the study by Campbell and de Jong (2001) who

sampled to a depth of 120 cm. For corn and soybeans

(Glycine max), root biomass in the upper 30 cm represented

95% of root biomass to a depth of 50 cm (Buyanovsky and

Wagner, 1986). For forages, Leyshon (1991) determined that

65% of the roots to a depth of 90 cm were in the upper

30 cm, and Bolinder et al. (2002) reported that the

proportion of roots in the deepest sampling layer (i.e.,

30–45 cm) remained constant at 10% during 2 years of

measurement. These distributions are similar to those for

mixed prairies of the northern Great Plains reported by

Lorenz (1977), who found that the upper 30 cm accounted

for 77% (n = 38) of roots to a depth of 122 or 152 cm.

Shoot-to-root ratios were calculated using the total

amounts of roots recovered in the various studies (Tables 1

and 2). For forage crops, the ‘shoot’ in this ratio was

calculated using the total biomass measured in all harvests

during the growing season (from one to four cuts per

season). Shoot and root data were expressed on a dry matter

basis; for studies that reported dry matter on both total and

ash-free basis, we used the latter. To calculate S:R ratios, we

assumed complete root recovery in all of the studies,

recognizing that some differences existed in sampling

protocols among studies. For annual crops, S:R ratios were

calculated from biomass measured at plant maturity. In

perennial forages the root biomass and S:R ratios may vary

with age of the stand (Weaver and Zink, 1946; Troughton,

1957; Hansson and Andrén, 1986) and the equilibrium

between net root growth and root turnover may not be

reached until 2–4 years after establishment (Troughton,

1957). Root biomass generally increases between the 1st and

2nd production year, typically by about 50% (Hansson and

Andrén, 1986; Pettersson et al., 1986), but this increase can

be much higher for some species (Bolinder et al., 2002).

Therefore, we assessed the forage S:R ratios by growth stage

(e.g., establishment year pure seeded, and 1 and 2 year after

establishment).

3. Proposed method for estimating total annual NPP,

C allocation, and C input to soil

3.1. NPP and C allocation

We propose a method for describing the accumulation

and distribution of C in crop plants. The criteria for this

method are:

1. I
t should include all plant C fractions. The sum of these
fractions should be a reasonable approximation of NPP

for agroecosystems, and allow direct comparison with

NPP of other ecosystems.

2. I
ts plant C fractions should be compatible with readily
available data, particularly with yield data widely

available for most agricultural crops.

3. I
t should allow direct and easy estimation of annual C
inputs to soil, for use in models of soil C dynamics in

response to crop type and management practices.

To meet these criteria, we apportioned the C in crop

plants into four fractions, expressed in units of mass C per

unit area per unit of time (e.g., g C m�2 yr�1) (Fig. 1):

CP p
lant C in the agricultural product, the plant portion of
primary economic value, and typically harvested and

exported from the ecosystem. The ‘product’ can be

either above-ground (e.g., grain, hay) or below-ground

(e.g., tuber). For forage crops, all exported above-

ground plant material is considered ‘product’.

CS p
lant C in straw, stover and other above-ground post-
harvest residue. This fraction includes all above-

ground plant materials excluding the ‘product’.

CR p
lant C in root tissue, comprised of all below-ground,
physically recoverable plant materials, excluding any

‘product’.

CE p
lant C in extra-root material, including root exudates
and other material derived from root-turnover, not

easily recovered by physically collecting, sieving or

removal. This fraction is roughly equivalent to that

sometimes referred to as ‘rhizodeposition’.

Now:

NPP ¼ CP þ CS þ CR þ CE (1)

The amount of C in each of these four fractions (and thus

also NPP) can be estimated from agricultural yields, using

published or assumed values for harvest index (HI), S:R

ratios, plant C in root exudates, and C concentrations in the

https://www.researchgate.net/publication/248446513_Above_and_below-ground_transformation_of_photosynthetically_fixed_carbon_by_two_barley_Hordeum_vulgare_L_cultivars_in_a_typic_cryoboroll?el=1_x_8&enrichId=rgreq-27196c30f5b3d8b4cf6acd1c1cde2e88-XXX&enrichSource=Y292ZXJQYWdlOzIxNjgwNDgzNjtBUzoxNjYwMjc1ODEyMDY1MjhAMTQxNjU5NTQ2ODY3NQ==https://www.researchgate.net/publication/233841570_Below-Ground_Plant_Production_in_a_Perennial_Grass_Ley_Festuca_pratensis_Huds_Assessed_with_Different_Methods?el=1_x_8&enrichId=rgreq-27196c30f5b3d8b4cf6acd1c1cde2e88-XXX&enrichSource=Y292ZXJQYWdlOzIxNjgwNDgzNjtBUzoxNjYwMjc1ODEyMDY1MjhAMTQxNjU5NTQ2ODY3NQ==https://www.researchgate.net/publication/233841570_Below-Ground_Plant_Production_in_a_Perennial_Grass_Ley_Festuca_pratensis_Huds_Assessed_with_Different_Methods?el=1_x_8&enrichId=rgreq-27196c30f5b3d8b4cf6acd1c1cde2e88-XXX&enrichSource=Y292ZXJQYWdlOzIxNjgwNDgzNjtBUzoxNjYwMjc1ODEyMDY1MjhAMTQxNjU5NTQ2ODY3NQ==https://www.researchgate.net/publication/233841570_Below-Ground_Plant_Production_in_a_Perennial_Grass_Ley_Festuca_pratensis_Huds_Assessed_with_Different_Methods?el=1_x_8&enrichId=rgreq-27196c30f5b3d8b4cf6acd1c1cde2e88-XXX&enrichSource=Y292ZXJQYWdlOzIxNjgwNDgzNjtBUzoxNjYwMjc1ODEyMDY1MjhAMTQxNjU5NTQ2ODY3NQ==https://www.researchgate.net/publication/231910724_Performance_of_conventional_and_alternative_cropping_systems_in_cryoboreal_subhumid_central_Alberta?el=1_x_8&enrichId=rgreq-27196c30f5b3d8b4cf6acd1c1cde2e88-XXX&enrichSource=Y292ZXJQYWdlOzIxNjgwNDgzNjtBUzoxNjYwMjc1ODEyMDY1MjhAMTQxNjU5NTQ2ODY3NQ==https://www.researchgate.net/publication/228587477_Root_biomass_and_shoot_to_root_ratios_of_perennial_forage_crops_in_eastern_Canada_Can_J_Plant_Sci?el=1_x_8&enrichId=rgreq-27196c30f5b3d8b4cf6acd1c1cde2e88-XXX&enrichSource=Y292ZXJQYWdlOzIxNjgwNDgzNjtBUzoxNjYwMjc1ODEyMDY1MjhAMTQxNjU5NTQ2ODY3NQ==https://www.researchgate.net/publication/228587477_Root_biomass_and_shoot_to_root_ratios_of_perennial_forage_crops_in_eastern_Canada_Can_J_Plant_Sci?el=1_x_8&enrichId=rgreq-27196c30f5b3d8b4cf6acd1c1cde2e88-XXX&enrichSource=Y292ZXJQYWdlOzIxNjgwNDgzNjtBUzoxNjYwMjc1ODEyMDY1MjhAMTQxNjU5NTQ2ODY3NQ==https://www.researchgate.net/publication/226552367_Post-harvest_residue_input_to_cropland?el=1_x_8&enrichId=rgreq-27196c30f5b3d8b4cf6acd1c1cde2e88-XXX&enrichSource=Y292ZXJQYWdlOzIxNjgwNDgzNjtBUzoxNjYwMjc1ODEyMDY1MjhAMTQxNjU5NTQ2ODY3NQ==https://www.researchgate.net/publication/226552367_Post-harvest_residue_input_to_cropland?el=1_x_8&enrichId=rgreq-27196c30f5b3d8b4cf6acd1c1cde2e88-XXX&enrichSource=Y292ZXJQYWdlOzIxNjgwNDgzNjtBUzoxNjYwMjc1ODEyMDY1MjhAMTQxNjU5NTQ2ODY3NQ==


plant parts. In a grain crop, for example, assuming the C

concentration of all plant parts is 0.45 g g�1:

CP ¼ YP � 0:45 (2)CS ¼ YPð1� HIÞ=HI� 0:45 (3)CR ¼ YP=ðS : R� HIÞ � 0:45 (4)CE ¼ CR � YE (5)

where YP is the dry matter yield of above-ground product

(g m�2 yr�1), HI the harvest index = dry matter yield of

grain/total above-ground dry matter yield, S:R the shoot:root

ratio, and YE is the extra-root C (rhizodeposit C), expressed

as factor relative to recoverable roots.

For perennial crops, root C persists from year to year.

Hence, CR is defined as the increase in root C in the year it

was established. Therefore, CR for perennial forage crops is

only included in NPP in the year of establishment. (This

assumes that CR does not increase after year 1.)

The allocation of C within different crop plant parts can also

be expressed using relative C allocation coefficients, esse-

ntially an expansion of HI, expressed as a proportion of NPP:

RP ¼ CP=NPP (6)RS ¼ CS=NPP (7)RR ¼ CR=NPP (8)RE ¼ CE=NPP (9)

By definition:

RP þ RS þ RR þ RE ¼ 1 (10)

These C allocation coefficients can be readily used to

calculate the corresponding value of CP, CS, CR, and CE,

if one of these (typically CP) is known:

CS ¼ ðRS=RPÞ � CP (11)

CR ¼ ðRR=RPÞ � CP (12)

CE ¼ ðRE=RPÞ � CP (13)

3.2. Annual C inputs to soil

In the simplest case, if only the ‘product’ is harvested, the

amount of C added to soil is estimated as: NPP � CP. Often,however, only a portion of some fractions is returned to the

soil. To account for that, we introduce an additional

parameter, S, which describes the proportion of the C in a

given fraction that is returned to soil. Typically, by default:

SP = 0, SS = 1, SR = 1, and SE = 1 (where SP, SS, SR, and SEare the proportions of C in product, above-ground residue,

roots, and extra-root C, respectively, that are returned to

soil). If a portion of a fraction is removed (e.g., wheat straw

removed for feed or bedding), then SS < 1. Thus:

Ci ¼ ½CP � SP� þ ½CS � SS� þ ½CR � SR� þ ½CE � SE� (14)

where Ci is the annual C input to soil.

In perennial forage crops, only a portion of the above-

ground vegetation is removed by grazing or harvest, hence

SP < 1. As well, there may be significant litter fall and harvestlosses, typically about 15% (e.g., Tomm et al., 1995), but these

can be reflected and adjusted in the SP factor. Since roots

persist from year to year for perennial forage crops, SR = 0,

except when the crop is discontinued (i.e., then SR = 1).

Relative C input (Ri), expressing C input to soil as a

proportion of NPP, is calculated as

Ri ¼ Ci=ðCP þ CS þ CR þ CEÞ (15)

3.3. Assumptions used in calculations

3.3.1. Harvest index

Harvest index values were estimated from studies across

Canada using the definition of Donald (1962), where grain

yield is expressed as a proportion of total above-ground

biomass on a dry weight basis. Thus:

HI ¼ YP=ðYP þ YSÞ (16)

Estimated HI values for annual crops (Table 5) ranged from a

low of 0.25 forgrain–sorghum to 0.63 for under-seeded barley.

3.3.2. Shoot:root ratios

The mean S:R ratios for annual crops were typically about

5, though values ranged from 1.1 to 10.7 (Table 3). There were

few consistent regional differences, except for barley

(Hordeum vulgare L.), which had a much lower S:R ratio

in eastern Canadian studies (2.0) than in western Canadian

studies (10.7). This difference may be attributable to the

effects of climate and varieties, or it may reflect, in part,

different approaches used in the extraction and measurement

of root biomass. Average S:R ratio in corn (5.6) was similar to

that of soybeans (5.2). The estimated S:R ratio for corn in

eastern Canada was higher than that in the U.S. studies.

Fertilization appears to have increased the S:R ratio. The

mean coefficient of variation (CV) for these location-

treatment combinations by crop type was approximately

50% (e.g., 49% for small-grain cereals, 42% for under-seeded

small-grain cereals, 50% for corn, and 60% for soybeans).

The mean S:R ratio of forages (Table 4) was typically 1–

2, much lower than that of annual crops. The S:R ratio for

legume species was nearly twice that of grass species. In

eastern Canada, the S:R ratio appeared to decrease with the

age of the stand, but this trend was not observed in western

Canada. The mean CV for forages was 75% (i.e., 77% for

grass species, 59% for legume species and 43% for mixtures

of the two), higher than that for the cereals and soybeans.

The higher variation in forage measurements may partly

reflect the difficulty in accurately sampling the dense and

diffuse root system of forages.

The Canadian data for forages were mostly from short-

term rotations (i.e., establishment year or first 4 production

years). Only the measurements by Leyshon (1991) were

from a long-term stand (i.e., 20 years); the mean S:R ratio for

https://www.researchgate.net/publication/250103376_Nitrogen_Cycling_in_an_Alfalfa_and_Bromegrass_Sward_via_Litterfall_and_Harvest_Losses?el=1_x_8&enrichId=rgreq-27196c30f5b3d8b4cf6acd1c1cde2e88-XXX&enrichSource=Y292ZXJQYWdlOzIxNjgwNDgzNjtBUzoxNjYwMjc1ODEyMDY1MjhAMTQxNjU5NTQ2ODY3NQ==https://www.researchgate.net/publication/269841261_Effect_of_rate_of_nitrogen_fertilizer_on_the_above-_and_below-ground_biomass_of_irrigated_bromegrass_in_southwest_Saskatchewan?el=1_x_8&enrichId=rgreq-27196c30f5b3d8b4cf6acd1c1cde2e88-XXX&enrichSource=Y292ZXJQYWdlOzIxNjgwNDgzNjtBUzoxNjYwMjc1ODEyMDY1MjhAMTQxNjU5NTQ2ODY3NQ==


Table 3

Summary and associated variability in measurements of shoot to root ratios

for small-grain cereals, corn and soybeans

Shoot/root

ratioan for

shoot/

root ratio

Small-grain

cereals

All studies 7.4 � 3.6 59Western Canada 8.5 � 3.2 41Eastern Canada 4.3 � 2.0 14

Spring wheat Western Canada 7.0 � 2.2 24Fertilized 5.6 � 0.1 22Unfertilized 7.1 � 2.3 2

Winter wheat Eastern Canada 6.0 � 1.2 6Winter wheat U.S. 1.1 � 0.1 3

Barley Western Canada 10.7 � 3.1 17Eastern Canada 2.0 � 0.3 3

Oats Eastern Canada 2.5 � 0.2 3Triticale Eastern Canada 5.4 � 0.4 2

Grain–sorghum U.S. 11.6 1

Under-seeded small-grain cereals

Barley Eastern Canada 3.1 � 1.3 10Barley

(Graminuous)

2.9 � 1.3 8

Barley

(Leguminuous)

4.2 � 0.6 2

Corn (grain and silage)

All studies 5.6 � 2.8 21Eastern Canada 9.5 � 1.4 4U.S.

Fertilized 4.7 � 2.1 17Unfertilized 3.6 � 1.3 4

Soybeans All studies (U.S.) 5.2 � 3.1 12a Mean � S.D.

Table 4

Summary and associated variability in measurements of shoot to root ratios

for cultivated forages

Shoot/root

ratioan for

shoot/root

ratio

Forages All studiesb 1.6 � 1.2 63Western Canada 1.2 � 1.3 24Eastern Canada 1.8 � 1.1 39

Grass species All studies 1.3 � 1.0 35Western Canada 0.6 � 0.4 9Eastern Canada 1.5 � 1.1 26

EYPSc Western Canada 0.2 1

1st PYd 0.9 � 0.5 32nd PY 0.1 1

EYPS Eastern Canada 2.2 � 1.3 101st PY 1.4 � 0.3 72nd PY 0.6 � 0.1 7

Legume species All studies 2.2 � 1.3 22Western Canada 2.2 � 1.6 9Eastern Canada 2.2 � 1.1 13

EYPS Western Canada 0.4 1

1st PY 0.7 1

2nd PY 0.7 1

EYPS Eastern Canada 2.7 � 0.9 91st PY 1.2 � 0.3 22nd PY 0.9 � 0.1 2

Mixture All studies 0.7 � 0.3 6EYPS Western Canada 0.6 � 0.1 21st PY 0.8 � 0.4 22nd PY 0.7 � 0.5 2

a Mean � S.D.b Excluding the U.S. data.c EYPS: establishment year pure seeded.d PY: production year (i.e., years after establishment).

that study was 0.6, with a range of 0.3–0.7 (Tables 2 and 4).

Stanton (1988) showed that S:R ratios for U.S. grasslands

varied from 0.1 to 0.5, with the lower values for cooler

climates. Bolinder et al. (2002) found that S:R ratios for

natural grasslands were between 0.2 and 1.8, but several

studies reported values near 0.5. Based on these findings, we

conclude that a S:R ratio of 0.5 is appropriate for long-term

prairie grasslands and pasture ecosystems in Canada.

3.3.3. Extra-root C

The plant C in root tissue at harvest (CR) is not the only

contribution from below-ground plant components to NPP

and annual C inputs. A significant, though poorly quantified,

proportion of NPP is released into the soil from the extra-

root (rhizodeposit) component (CE). This material includes

exudates, as well as root hairs and fine roots sloughed off

during the growing season which, because of sampling

difficulties, are not included in the ‘root’ fraction.

Recent reviews of tracer studies indicates that roughly

33% of C allocated below-ground in wheat and barley is

released by living roots and remains in soil (including in the

soil microbial biomass), and that 50% of below-ground C

remains in roots (Kuzyakov and Domanski, 2000; Kuzyakov

and Schneckenberger, 2004). This implies that CE � 0.65(i.e., 33/50) � CR, but values varied widely among studies.As a preliminary estimate for small-grain cereals, corn, and

soybean, we assume, that CE = 0.65 � CR. This estimate ismore conservative than those presented in earlier studies.

For example, some studies of annual crops (corn and small-

grain cereals) assumed that extra-root C (rhizodeposited C)

is equal to root C; that is: CE = CR (Barber, 1979; Bolinder

et al., 1997, 1999; Plénet et al., 1993), based on studies by

Barber and Martin (1976) and Sauerbeck and Johnen (1977).

Most studies of C from rhizodeposition in perennial

forages have considered only pastures and natural grass-

lands. In reviewing the literature on root C inputs, Kuzyakov

and Domanski (2000) concluded that the rhizodeposition in

pastures was comparable to that in small-grain cereals (i.e.,

CE = 0.65 � CR). Gill et al. (2002) concluded that in naturalgrasslands about 65% of roots die and detach every year.

https://www.researchgate.net/publication/45530807_Evolution_a_long_terme_du_statut_carbone_du_sol_en_monoculture_non_irriguee_du_mais_Zea_mays_L?el=1_x_8&enrichId=rgreq-27196c30f5b3d8b4cf6acd1c1cde2e88-XXX&enrichSource=Y292ZXJQYWdlOzIxNjgwNDgzNjtBUzoxNjYwMjc1ODEyMDY1MjhAMTQxNjU5NTQ2ODY3NQ==https://www.researchgate.net/publication/248351777_Estimating_shoot_to_root_ratios_and_annual_carbon_inputs_in_soil_for_cereal_crops?el=1_x_8&enrichId=rgreq-27196c30f5b3d8b4cf6acd1c1cde2e88-XXX&enrichSource=Y292ZXJQYWdlOzIxNjgwNDgzNjtBUzoxNjYwMjc1ODEyMDY1MjhAMTQxNjU5NTQ2ODY3NQ==https://www.researchgate.net/publication/248351777_Estimating_shoot_to_root_ratios_and_annual_carbon_inputs_in_soil_for_cereal_crops?el=1_x_8&enrichId=rgreq-27196c30f5b3d8b4cf6acd1c1cde2e88-XXX&enrichSource=Y292ZXJQYWdlOzIxNjgwNDgzNjtBUzoxNjYwMjc1ODEyMDY1MjhAMTQxNjU5NTQ2ODY3NQ==https://www.researchgate.net/publication/251844237_Review_of_estimation_of_plant_rhizodeposition_and_their_contribution_to_soil_organic_matter_formation_Arch_Agron_Soil_Sci?el=1_x_8&enrichId=rgreq-27196c30f5b3d8b4cf6acd1c1cde2e88-XXX&enrichSource=Y292ZXJQYWdlOzIxNjgwNDgzNjtBUzoxNjYwMjc1ODEyMDY1MjhAMTQxNjU5NTQ2ODY3NQ==https://www.researchgate.net/publication/251844237_Review_of_estimation_of_plant_rhizodeposition_and_their_contribution_to_soil_organic_matter_formation_Arch_Agron_Soil_Sci?el=1_x_8&enrichId=rgreq-27196c30f5b3d8b4cf6acd1c1cde2e88-XXX&enrichSource=Y292ZXJQYWdlOzIxNjgwNDgzNjtBUzoxNjYwMjc1ODEyMDY1MjhAMTQxNjU5NTQ2ODY3NQ==https://www.researchgate.net/publication/235708817_Using_simple_environmental_variables_to_estimate_below-_ground_productivity_in_grasslands?el=1_x_8&enrichId=rgreq-27196c30f5b3d8b4cf6acd1c1cde2e88-XXX&enrichSource=Y292ZXJQYWdlOzIxNjgwNDgzNjtBUzoxNjYwMjc1ODEyMDY1MjhAMTQxNjU5NTQ2ODY3NQ==https://www.researchgate.net/publication/240782834_Corn_Residue_Management_and_Soil_Organic_Matter1?el=1_x_8&enrichId=rgreq-27196c30f5b3d8b4cf6acd1c1cde2e88-XXX&enrichSource=Y292ZXJQYWdlOzIxNjgwNDgzNjtBUzoxNjYwMjc1ODEyMDY1MjhAMTQxNjU5NTQ2ODY3NQ==https://www.researchgate.net/publication/227083737_Estimating_C_inputs_retained_as_soil_organic_matter_from_corn_Zea_Mays_L?el=1_x_8&enrichId=rgreq-27196c30f5b3d8b4cf6acd1c1cde2e88-XXX&enrichSource=Y292ZXJQYWdlOzIxNjgwNDgzNjtBUzoxNjYwMjc1ODEyMDY1MjhAMTQxNjU5NTQ2ODY3NQ==https://www.researchgate.net/publication/248643388_The_release_of_organic_substances_by_cereal_roots_into_soil_New_Phytol?el=1_x_8&enrichId=rgreq-27196c30f5b3d8b4cf6acd1c1cde2e88-XXX&enrichSource=Y292ZXJQYWdlOzIxNjgwNDgzNjtBUzoxNjYwMjc1ODEyMDY1MjhAMTQxNjU5NTQ2ODY3NQ==https://www.researchgate.net/publication/228587477_Root_biomass_and_shoot_to_root_ratios_of_perennial_forage_crops_in_eastern_Canada_Can_J_Plant_Sci?el=1_x_8&enrichId=rgreq-27196c30f5b3d8b4cf6acd1c1cde2e88-XXX&enrichSource=Y292ZXJQYWdlOzIxNjgwNDgzNjtBUzoxNjYwMjc1ODEyMDY1MjhAMTQxNjU5NTQ2ODY3NQ==


Thus, for perennial forages, we also assume that

CE = 0.65 � CR.Our estimates of extra-root C have high uncertainty

reflecting the variability of measured values. Nevertheless, we

present these estimates as a first approximation, recognizing

that more reliable estimates emerging from further research

can be easily incorporated into our approach.

4. Discussion

4.1. Relative C allocation coefficients for Canadian

agroecosystems

The relative C allocation coefficients (RP, RS, RR, RE) and

relative C input (Ri), which expresses C input as a proportion

of NPP, were calculated for a range of crops under Canadian

Table 6

Relative annual plant C allocation coefficients for perennial forage crops and silage

Crop type Relative plant C allocation coefficients

RP RS

Perennial forages 0.492 0.000

Grass species 0.441 0.000

Legume species 0.571 0.000

Mixture 0.298 0.000

Grassland/pasture 0.233 0.000

Silage–cornb 0.772 0.000

a The minimum value represents calculations for a forage crop that is not disco

have been discontinued (see the text). For a continuous forage crop we considered t

(SP = 0.15; representing the proportion of above-ground plant parts returned to the

when it is discontinued (i.e., at that time an additional 10% is left behind in the fi

biomass was removed (SP = 0.05).b We used the same shoot to root ratio for both grain– and silage–corn.

Table 5

Relative annual plant C allocation coefficients for small-grain cereals, grain–co

agroecosystems

Crop type HIa (%) Relative plant C allocation

RP RS

Small-grain cereals 41 0.335 0.482

Wheatc 40 0.322 0.482

Barley 53 0.451 0.400

Oats 53 0.319 0.283

Triticale 34 0.260 0.506

Grain–sorghum 25 0.219 0.656

Under-seeded small-grain cereals

Barley 63 0.411 0.241

Grain–corn 50 0.386 0.387

Soybeans 40 0.304 0.455

Relative plant C allocation coefficients : RP = CP/NPP, RS = CS/NPP, RR = CR/NPa Sources: Izaurralde et al. (2001), Campbell and Zentner (1993), Bolinder et al.

and Wagner (1986) and Schapaugh and Wilcox (1980).b The minimum of the range specified assumes all recoverable above-ground ma

for grain–corn and soybeans; representing the proportion of above-ground plant p

assumes all material, except for plant products are returned to the soil.c Only the Canadian data for S:R were used.

conditions (Tables 5 and 6). For small-grain cereals

(Table 5), we estimated a range of Ri values, spanning full

removal to full retention of above-ground residues. For

perennial forage crops (Table 6), the minimum value for Rirepresents the C input from a forage crop that is continued,

and the maximum value is that for a forage crop that is

discontinued. Because there were few consistent differences

in S:R ratios between regions (Tables 3 and 4), we calculated

mean values for the country. The RR value we used for

forages (Table 6) was estimated from the average of the S:R

ratios (Table 4) from the studies where forages were grown

in short-term rotations (i.e., in the establishment year or 1st

production years).

Our estimates of maximum Ri (where all residues are

returned to soil) ranged from 0.55 to 0.78 for annual crops

(Table 5). Estimates of minimum Ri values for small-grain

cereals (where all manageable residues are removed) ranged

–corn used to estimate NPP and C input to soil for Canadian agroecosystems

Relative proportion (Ri)

of NPP returned to soilaRR RE

0.308 0.200 0.27–0.63

0.339 0.220 0.29–0.67

0.260 0.169 0.26–0.57

0.426 0.277 0.32–0.78

0.465 0.302 0.34

0.138 0.090 0.27

ntinued; the maximum value assumes that the perennial forage crops would

hat the harvested hay represented 85% of the total above-ground production

soil as litter fall and harvest losses) and that it represented 75% (SP = 0.25)

eld as stubble). For silage–corn we assumed that 95% of the above-ground

rn and soybeans used to estimate NPP and C input to soil for Canadian

coefficients Relative proportion (Ri)

of NPP returned to soilbRR RE

0.110 0.073 0.26–0.67

0.118 0.078 0.27–0.68

0.090 0.059 0.21–0.55

0.241 0.157 0.44–0.68

0.142 0.092 0.31–0.74

0.075 0.050 0.22–0.78

0.211 0.137 0.38

0.138 0.089 0.27–0.61

0.146 0.095 0.29–0.70

P, RE = CE/NPP (see the text).

(1997, 1999), Kunelius et al. (1992), Piper and Kulakow (1994), Buyanovsky

terial is exported (calculated with SS = 0.15 for small-grain cereals and 0.10

arts returned to the soil as stubble and other surface debris); the maximum

https://www.researchgate.net/publication/248351777_Estimating_shoot_to_root_ratios_and_annual_carbon_inputs_in_soil_for_cereal_crops?el=1_x_8&enrichId=rgreq-27196c30f5b3d8b4cf6acd1c1cde2e88-XXX&enrichSource=Y292ZXJQYWdlOzIxNjgwNDgzNjtBUzoxNjYwMjc1ODEyMDY1MjhAMTQxNjU5NTQ2ODY3NQ==https://www.researchgate.net/publication/237589329_Carbon_Balance_of_the_Breton_Classical_Plots_over_Half_a_Century?el=1_x_8&enrichId=rgreq-27196c30f5b3d8b4cf6acd1c1cde2e88-XXX&enrichSource=Y292ZXJQYWdlOzIxNjgwNDgzNjtBUzoxNjYwMjc1ODEyMDY1MjhAMTQxNjU5NTQ2ODY3NQ==https://www.researchgate.net/publication/227083737_Estimating_C_inputs_retained_as_soil_organic_matter_from_corn_Zea_Mays_L?el=1_x_8&enrichId=rgreq-27196c30f5b3d8b4cf6acd1c1cde2e88-XXX&enrichSource=Y292ZXJQYWdlOzIxNjgwNDgzNjtBUzoxNjYwMjc1ODEyMDY1MjhAMTQxNjU5NTQ2ODY3NQ==https://www.researchgate.net/publication/240401435_Effect_of_undersowing_barley_with_Italian_ryegrass_or_red_clover_on_yield_crop_composition_and_root_biomass?el=1_x_8&enrichId=rgreq-27196c30f5b3d8b4cf6acd1c1cde2e88-XXX&enrichSource=Y292ZXJQYWdlOzIxNjgwNDgzNjtBUzoxNjYwMjc1ODEyMDY1MjhAMTQxNjU5NTQ2ODY3NQ==


Fig. 2. Comparison between total net primary productivity estimated for

boreal forests with the CBM–CFS2 model (data from Li et al. (2003)) and

that of the average estimated with the proposed method for some annual

crops (grain–corn, soybeans and small-grain cereals) commonly grown in

Canadian prairie agroecosystems for the period 1991–1995.

from 0.21 to 0.44. The relative proportion of NPP returned to

soil for perennial forage (Table 6), depends on whether this

crop is continued or discontinued. The Ri for perennial

forages (continued), silage–corn, and grassland/pasture was

about 0.30. In the year of termination, forage crops had

much higher Ri values (0.57–0.78), similar to the maximum

Ri for annual crops.

The proportion of NPP as BNPP (i.e., RR + RE) (Tables 5

and 6) was, on average, 18% for small-grain cereals, 23% for

corn, 24% for soybeans, and 51% for perennial forages (in

the year of establishment). These values are slightly lower

than those of natural ecosystems: 48–64% for a tallgrass

prairie, 70–78% in a shortgrass prairie and 61–80% of NPP

for a mixed-grassland ecosystem (Stanton, 1988). For forest

ecosystems, Li et al. (2003) reviewed above- and below-

ground data in the literature for softwood (n = 340) and

hardwood (n = 103) species grown on the Canadian Prairie

Provinces. They found that BNPP as a proportion of NPP

was 55% for subactic, 46% for boreal forests, 43% for

grassland and 48% for cordilleran forests. On average, for

the entire region, the BNPP estimate for forests represented

47% of total NPP, lower than in an earlier estimate (Kurz

et al., 1996). Our findings suggest that relative BNPP

allocation in perennial forage crops in Canada is comparable

to that in Canadian forest ecosystems.

4.2. Quantitative estimates of annual C inputs to soil

and NPP

Although comparing relative C allocation patterns among

different Canadian agroecosystems is useful, for modelling

soil C changes in agricultural soils we need to estimate the

actual amount of C inputs (Ci) entering the soil. Indeed, C

input is one of the most important driving variables for

predicting the net rate of soil C change (Bolinder et al.,

2006).

To illustrate the variability in estimates of C inputs for

crops in Canadian agroecosystems, we used the proposed

method to calculate Ci for small-grain cereals and perennial

forages. We assumed a grain yield of 4 Mg DM ha�1 (i.e.,

CP = 180 g C m�2) and a total annual hay yield of

8 Mg DM ha�1 (i.e., CP = 360 g C m�2), values typical of

eastern Canadian farms.

Using Eqs. (11)–(13) for small-grain cereals and

coefficients from Table 5:

CS ¼ ð0:482=0:335Þ � 180 ¼ 259 g C m�2;

CR ¼ ð0:110=0:335Þ � 180 ¼ 59 g C m�2;

CE ¼ ð0:073=0:335Þ � 180 ¼ 39 g C m�2

From Eq. (14), if all residue is returned to soil:

Ci ¼ ½180� 0� þ ½259� 1� þ ½59� 1� þ ½39� 1�

¼ 357 g C m�2

And if residues are removed:

Ci ¼ ½180� 0� þ ½259� 0:15� þ ½59� 1� þ ½39� 1�

¼ 137 g C m�2

In the same manner, using Eqs. (11)–(14) generates esti-

mates of Ci = 462 g C m�2 if the forage crop is discontin-

ued, but only Ci = 200 g C m�2 if it is continued. This

example shows the key role of management on C inputs,

and illustrates how decisions about straw removal or dura-

tion of forage crop stands may affect the C input as much (or

more than) the type of crop grown.

We also used the proposed method to compare estimates

of NPP for agroecosystems with those of forest ecosystems

(Fig. 2), using data from Li et al. (2003), who calculated NPP

for boreal forests in Manitoba, Saskatchewan and Alberta

with the Carbon Budget Model of the Canadian Forest

Sector (CBM-CFS2). Their model estimates were compared

to average NPP estimates we calculated (Eqs. (1), (11)–(13))

for some annual agricultural crops in the same provinces and

time-period (1991–1995) using average yield data from

Statistics Canada. The results showed that the average NPP

of annual crops was slightly higher than that for boreal

forests (though, admittedly, climate and soils are not directly

comparable for the two biomes). In this example, highest

NPP for both boreal forests and annual crops was in Alberta.

4.3. Uncertainty associated with estimates of BNPP

There is substantial uncertainty in the estimates of BNPP

and, as a consequence, the C inputs derived from those

estimates. The mean CV for S:R ratios was as high as 50% for

annual crops (Table 3) and 75% for perennial forages

(Table 4). However, this uncertainty in estimates of BNPP is

common also in other ecosystems. For example, Williams

et al. (2005) estimated that the error for fine root biomass for a

https://www.researchgate.net/publication/249534353_Kurz_W_A_Beukema_S_J_Apps_M_J_Estimation_of_root_biomass_and_dynamics_for_the_carbon_budget_model_of_the_Canadian_forest_sector_Can_J_For_Res_26_1973-1979?el=1_x_8&enrichId=rgreq-27196c30f5b3d8b4cf6acd1c1cde2e88-XXX&enrichSource=Y292ZXJQYWdlOzIxNjgwNDgzNjtBUzoxNjYwMjc1ODEyMDY1MjhAMTQxNjU5NTQ2ODY3NQ==https://www.researchgate.net/publication/249534353_Kurz_W_A_Beukema_S_J_Apps_M_J_Estimation_of_root_biomass_and_dynamics_for_the_carbon_budget_model_of_the_Canadian_forest_sector_Can_J_For_Res_26_1973-1979?el=1_x_8&enrichId=rgreq-27196c30f5b3d8b4cf6acd1c1cde2e88-XXX&enrichSource=Y292ZXJQYWdlOzIxNjgwNDgzNjtBUzoxNjYwMjc1ODEyMDY1MjhAMTQxNjU5NTQ2ODY3NQ==https://www.researchgate.net/publication/216805006_Modelling_soil_organic_carbon_stock_change_for_estimating_whole-farm_greenhouse_gas_emissions?el=1_x_8&enrichId=rgreq-27196c30f5b3d8b4cf6acd1c1cde2e88-XXX&enrichSource=Y292ZXJQYWdlOzIxNjgwNDgzNjtBUzoxNjYwMjc1ODEyMDY1MjhAMTQxNjU5NTQ2ODY3NQ==https://www.researchgate.net/publication/216805006_Modelling_soil_organic_carbon_stock_change_for_estimating_whole-farm_greenhouse_gas_emissions?el=1_x_8&enrichId=rgreq-27196c30f5b3d8b4cf6acd1c1cde2e88-XXX&enrichSource=Y292ZXJQYWdlOzIxNjgwNDgzNjtBUzoxNjYwMjc1ODEyMDY1MjhAMTQxNjU5NTQ2ODY3NQ==https://www.researchgate.net/publication/227790872_An_improved_analysis_of_forest_carbon_dynamics_using_data_assimilation_Glob_Change_Biol?el=1_x_8&enrichId=rgreq-27196c30f5b3d8b4cf6acd1c1cde2e88-XXX&enrichSource=Y292ZXJQYWdlOzIxNjgwNDgzNjtBUzoxNjYwMjc1ODEyMDY1MjhAMTQxNjU5NTQ2ODY3NQ==https://www.researchgate.net/publication/227790872_An_improved_analysis_of_forest_carbon_dynamics_using_data_assimilation_Glob_Change_Biol?el=1_x_8&enrichId=rgreq-27196c30f5b3d8b4cf6acd1c1cde2e88-XXX&enrichSource=Y292ZXJQYWdlOzIxNjgwNDgzNjtBUzoxNjYwMjc1ODEyMDY1MjhAMTQxNjU5NTQ2ODY3NQ==


ponderosa pine stand in Oregon (U.S.) was �30%.Furthermore, Cairns et al. (1997) compiled worldwide

literature estimates for broadleaf (n = 102) and coniferous

(n = 63) forests and reported that the coefficient of variation of

S:R ratios varied between 27 and 48%, with the greater

variation observed for broadleaf forests. The high levels of

uncertainty in BNPP estimates suggest that both improvement

and standardization of sampling procedures are required for

more accurate estimates. Even then, high uncertainty in BNPP

of terrestrial ecosystems is likely to remain.

To quantify the uncertainty associated with the root C

inputs using the proposed approach, we estimated the total C

inputs for grain–corn and soybean crops with average yields

(8 Mg grain ha�1 for grain–corn and 5 Mg ha�1 for soy-

beans). We used the mean and standard deviation of S:R

ratios for these crops (i.e., 5.6 � 2.8 for grain–corn and5.2 � 3.1 for soybeans; Table 3) to calculate the relativeplant C allocation coefficients. The HI was held constant

(50% for corn, 40% for soybeans; Table 5) so that the

amount of above-ground C inputs estimated using the mean,

highest and lowest S:R ratio was the same (Fig. 3a and b).

The above-ground C inputs for these two crops are

Fig. 3. (a) Uncertainty related to the annual C input from BNPP (CR and CE) c

Uncertainty related to the annual C input from BNPP (CR and CE) component f

substantial; with the mean S:R ratio, the quantity of

above-ground C inputs is greater than that from below-

ground plant material. But the uncertainty associated with

the S:R ratios shows that there is considerable variability

related to estimates of below-ground C inputs. Taking this

variability into account generated estimates as low as

142 g C m�2 yr�1 or as high as 424 g C m�2 yr�1 for corn

(D = 282 g C m�2 yr�1), and as low as 112 g C m�2 yr�1 oras high as 442 g C m�2 yr�1 for soybeans (D = 330 g

C m�2 yr�1). These large differences in C inputs show

how crucial better estimates of BNPP are in predicting

changes in soil organic C more accurately.

The variability associated with HI would also affect

estimates of C inputs to the soil. To evaluate how variation in

HI (and the associated variation in S:R ratio) would affect

our estimates of C input, we varied the HI from 35 to 45% for

calculating C inputs from soybeans (Fig. 3b). Using this

range of HI values, typical of those measured for various

crops (Hay, 1995), and holding the S:R ratio constant at 5.2,

resulted in a low estimate of 275 g C m�2 yr�1 and a high

estimate of 418 g C m�2 yr�1 for above-ground C inputs

(i.e., D = 143 g C m�2 yr�1). The difference in C inputs

omponent for an average yielding grain–corn crop (8 Mg grain ha�1). (b)

or an average yielding soybean crop (5 Mg grain ha�1).


from variation in HI is much lower than that from variation

in the S:R ratio (i.e., 330 g C m�2 yr�1; Fig. 3b). Prince et al.

(2001) observed that variations in HI had a larger effect than

variations in R:S ratios on NPP estimates in agricultural

regions of the U.S. Midwest. In a sensitivity analysis they

considered a 10% deviation for both the HI and S:R ratio

(e.g., actual HI � 0.1 � actual HI), and concluded that onlylarge deviations of �50% in R:S ratios would have asignificant affect on the estimates of NPP. Our data suggest

that S:R ratios may, in fact, have such high variability,

indicating that uncertainty related to BNPP is significant for

agroecosystems.

5. Conclusions

The method proposed here for estimating NPP and annual

C inputs to soil for Canadian agroecosystems is straight-

forward and easy to use. More importantly, however, the

plant C allocation coefficients can be updated readily and

estimates can be refined as new measurements emerge. The

uncertainty associated with the below-ground C is sub-

stantial, and reflects our knowledge (or lack thereof,

especially with regard to BNPP). Additional field measure-

ments are therefore needed to reduce uncertainty for the

estimates of root biomass and S:R ratios that are used to

calculate BNPP. There are two advantages in assessing the

range of uncertainty in C inputs. First, it can help account for

variations in the predictions of C storage using simulation

models. Secondly, the maximum C inputs for a particular

cropping system define the upper boundaries for soil organic

C sequestration rates; that is, you cannot sequester more C in

soil than is added via photosynthesis.

Acknowledgement

The Model Farm Program for Canadian Agriculture

project provided funding for this work. Thanks are extended

to Drs. O. Andrén and T. Kätterer for comments and

discussion on an earlier draft of this paper.

Appendix A. Supplementary data

Supplementary data associated with this article can be

found, in the online version, at doi:10.1016/j.agee.2006.

05.013.

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An approach for estimating net primary productivity and ......Review An approach for estimating net primary productivity and annual carbon inputs to soil for common agricultural crops